Conventionally, measures of arterial oxygen saturation (also referred to as O2 saturation) are produced using the well-known technique of pulse oximetry in the following manner. Light of two different wavelengths, typically red (e.g., about 660 nm wavelength) and infrared or near infrared (e.g., about 940 nm wavelength), are alternately transmitted through or reflected by patient tissue such that a light detector receives incident light that alternates between red and infrared light. More specifically, one LED transmits red light and an another LED that transmits infrared or near infrared light. The LEDs are serially pulsed to produce an interleaved signal stream that is transmitted through or reflected from tissue of a patient. As the light passes through and/or is reflected from tissue, some of the energy is absorbed by arterial and venous blood, tissue and the variable pulsations of arterial blood. The interleaved red and infrared light stream is received by the light detector. The amplitudes of the red light pulses in the light stream are differently effected by the absorption than the infrared light pulses, with the absorptions levels depending on the O2 saturation level of the blood.
Using electronic circuitry, firmware and/or software, the received light signals in the infrared and red wavelengths are analyzed so that O2 saturation levels can be determined. At a high level, demultiplexing is used to produce a signal path for the received red light and a separate signal path for the received infrared light. Each signal path will typically include one or more filters and an analog-to-digital (A/D) converter to sample the received light signals. More specifically, each signal is typically filtered, amplified and converted to a digital signal using an (A/D) converter (not necessarily in this order). For example, each signal may be sampled at 500 Hz (i.e., 500 samples per second) using a high resolution A/D converter, and then the samples may undergo relatively intensive post-acquisition digital filtering (e.g., using a 1000-point filter).
The samples of the red light signal are then used to determine the DC offset (i.e., average) and pulse amplitude of the received red light. Similarly, the samples of the infrared light signal are then used to determine the DC offset (i.e., average) and pulse amplitude of the received infrared light. Each pulse amplitude is then normalized (e.g., by dividing the pulse amplitude by the corresponding DC offset) and a ratio of the red-to-infrared light is determined by dividing the normalized red pulse amplitude by the normalized infrared pulse amplitude. Then, a one dimensional look-up table is typically used to determine the O2 saturation level. Such a look-up table is typically used because there is a well known one-to-one correspondence between the red-to-infrared ratios and O2 saturation levels.
Recently there has been interest in using implantable devices to obtain measures of O2 saturation. Exemplary patents that indicate such interest include, e.g., U.S. Pat. No. 5,040,533 (Fearnot) and U.S. Pat. No. 5,556,421 (Prutchi et al.), both of which concentrate of mechanical features of the implantable devices.
While the above described conventional scheme for obtaining measures of O2 saturation have worked well for non-implanted devices, it would be beneficial if the amount of processing and power consumption can be reduced to a level acceptable for implantable devices. More specifically, the relatively intensive processing associated with conventional pulse oximetry techniques consume large amounts of power and processing resources. While this may not be much of a concern with non-implanted pulse oximetry devices, minimizing power consumption and processing is very important when it comes to implantable devices. This is in part because invasive surgery is required to replace the battery of an implanted device. Accordingly, there is a desire to reduce, and hopefully minimize, both the processing required to obtain measures of O2 saturation using an implantable device, which in turn will reduce and hopefully minimize power consumption.